"Proponents of ‘democratic news recommender design’ argue that algorithmic news diversification may facilitate democratic participation. However, while various news diversification metrics have been proposed in recent years, few of them have been put to the test with real users. To assess the pr
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omises and pitfalls of algorithmic news diversification, we conduct a 2 (low vs. high levels of activating language) by 3 (low vs medium vs high levels of alternative voices) between subjects experiment with N = 715 respondents to test how normatively driven news diversification affects readers’ (a) policy support, (b) outcome tolerance, (c) outgroup tolerance, and (d) political participation. Results show that in a one-off experiment, exposure diversity has at best very small effects on the dependent variables when demographic and attitudinal characteristics are controlled for. We also find that extreme forms of news diversification may impede user satisfaction." (Abstract)
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"Few would disagree that AI systems and applications need to be “responsible,” but what is “responsible” and how to answer that question? Answering that question requires a normative perspective on the role of journalistic AI and the values it shall serve. Such a perspective needs to be grou
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nded in a broader normative framework and a thorough understanding of the dynamics and complexities of journalistic AI at the level of people, newsrooms and media markets. This special issue aims to develop such a normative perspective on the use of AI-driven tools in journalism and the role of digital journalism studies in advancing that perspective. The contributions in this special issue combine conceptual, organisational and empirical angles to study the challenges involved in actively using AI to promote editorial values, the powers at play, the role of economic and regulatory conditions, and ways of bridging academic ideals and the messy reality of the real world. This editorial brings the different contributions into conversation, situates them in the broader digital journalism studies scholarship and identifies seven key-take aways." (Abstract)
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"[...] this study provides an extensive overview of conceptualizations and operationalizations of media diversity in different fields using a systematic literature review (1999–2018). This showed a lack of theorizing and linking of conceptual with empirical work in media diversity research. Based
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on this, we develop a framework on how to move forward: Regarding conceptualization, we call for focusing on different places in the journalistic information chain instead of the classical exposure-supply distinction. Methodologically, automated approaches (e.g., analyzing digital traces) and qualitative approaches (e.g., capturing perceptions of diversity) should receive more attention. For analysis, matters of balance and disparity need to be stressed more, especially discussing possible limits to diversity. Overall, research into media diversity thus needs to be addressed in interdisciplinary collaboration." (Abstract)
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"Based on an analysis of the use of AI-driven tools in the light of Article 10 EHCR, this report highlights a number of points for attention and the need for further initiatives. In particular, we signal that:
- There is an important role for member States to ensure that access to innovative technol
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ogies, training data, digital skills and education in the use of new data-driven means of producing and distributing news is also open to smaller, local players. This is important also in the light of the growing competition with new media players, such as internet intermediaries, and the need to protect and promote diverse media markets.
- While the use of AI-driven tools in the media is in principle covered by Article 10 ECHR, the protection afforded under Article 10 ECHR also comes with specific duties and responsibilities for the media. In particular, we signal the need to and make concrete proposals for the development of professional algorithmic ethics regarding the question of how to promote the use of AI-driven tools in a way that is compatible with human rights and fundamental freedoms.
- In addition to the development of professional algorithmic ethics, the positive obligations of member States include the need to identify clear conditions for the responsibility and (editorial) oversight regarding automated processes, be that AI-driven recommendations in the media, media intermediaries or robot journalism, but also for creating fair conditions for the media to flourish in data-driven media markets." (Executive summary, page 3)
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